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Data Science Recruitment Survey 2020 (Job Seekers Perspective): By AIM & AnalytixLabs

Data Science Recruitment Survey 2020 (Job Seekers Perspective): By AIM & AnalytixLabs

Siddhartha Thomas

Data scientists, data engineers, and business analysts are now among the most sought-after positions across functions – analytics is a sought-after function across industries covering IT, Consulting, BFSI, and e-commerce, Fintech, to name a few.

While applying for jobs many applicants face the following challenges – what are the challenges that jobs seekers face during the recruitment process; what are the target industries that applicants would like to join; what are the best approaches to get an entry-level job in Data Science? How easy is to transition to a Data Science role form a Non-Science background? All these questions, and many others, are best answered by the people who face these situations first-hand – Data Science and Analytics job seekers.

This research is done in collaboration with AnalytixLabs, a leading analytics education institute in India. As part of the efforts to determine the challenges applicants face during the Data Science and Analytics hiring process, AIM released this recruitment survey aimed at job seekers across the Data Science community.

This year the survey was focused only at job applicants / job seekers. Moreover, this year social media channels were utilized to reach out to a wider audience.

AIM has now published the findings of the survey in this report. The findings cover some of the experiences of Data Science and Analytics job seekers, including the challenges faced during the current downturn and reduced demand for analytics services.

Benefits & Takeaways In The Current Scenario

At the beginning of the year, there was a sharp increase in the demand for Analytics professionals. The open jobs figure for analytics reached a maximum in February – March 2020 – reaching a high of approximately 113,000 in the 1st week of March, rising steadily from a figure of 97,000 last year. However, the lockdown and the ensuing recession reduced the open job numbers bringing the figures down to an average of 80,000 in May-June. A once thriving recruitment market has been affected by the recession (a recession caused by the Covid – 19 pandemic).

This survey provides a direct perspective on the recruitment scenario from the perspective of Data Science and Analytics job seekers. This report will benefit prospective job seekers, including students, to understand the outlook of the broad Analytics job market – including best approaches to apply for jobs, the sites and resources commonly used by job seekers, the tools or approaches used to up-skill or prepare for an interview, and the cities that offer the best opportunities for Data Scientists, to name a few perspectives. All these viewpoints are especially important to understand in the current recruitment scenario, which is relatively subdued.

Key Findings

Jobs Availability in the Current Crisis

The jobs seekers’ experience and perspective on the availability of data science jobs in the current crisis remains mixed, as there are respondents who believe that jobs will take some time to emerge, while others believe that jobs are available. 37% of the respondents believe that Data Science Jobs are Available, which is the highest and most optimistic response for all those surveyed.

Of the rest of the respondents surveyed, 16% believe that Jobs Might Not Emerge for 1 Year – this is the most pessimistic of views of those surveyed. 21% believe that Jobs Might Not Emerge for 6 months – this is the 2nd most pessimistic view of those surveyed. 18% believe that Jobs Might Emerge in 3 months, while 8% of the respondents believe that Jobs Might Emerge in 1 Month.

These figures clearly indicate that more than a third of the respondents surveyed believe that Analytics and Data Science jobs are available – a largely optimistic first-hand view from job seekers.

Challenges Encountered During the Data Science Recruitment Process

There are many challenges that data science job seekers face during the hiring process. Of these, the most challenging is the Lengthy Hiring Process for 39% of the job seekers. Lack of Regular Communication from Recruiters is listed as the 2nd most challenging as about 28% of the respondents face this challenge. This covers the end-to-end process of recruitment, including the time or gap between rounds, or any positive or negative feedback at the end of the entire process.

This is followed by 25% of the respondents experience Insufficient Evaluation of Data Science skills – these specific job seekers have responded that the recruitment process covers a more rounded evaluation process rather than a specific skills appraisal – according to the job seekers the process should evaluate Data Science and Technical skills rather than generic skills.

Lack of post-hiring onboarding is a challenge that 9% of the job seekers face. This covers a possible detailed briefing on the job or role that the successful applicant is expected to perform, and the processes of training and overall onboarding that need to take place post-hiring. Other challenges are listed by 15% of the respondents.

Necessity of Degree or Formal Education for a Data Science Job / Career

The necessity of a Degree or Formal Education for Analytics and Data Science hiring is identified by 35% of the respondents. This is a straight-forward response from the survey takers as formal education lays the foundation for a career in any given field.

About 23% of the respondents believe that Online Certifications and Courses are Sufficient for Hiring in Data Science. Given the shift to decentralized learning and self-paced instruction, this option is gaining popularity across the Data Science community.

17% of the respondents believe that on-the-job learning with no formal learning is sufficient for a career in Data Science. While 13% of the respondents believed that Free Online Courses are sufficient for data science hiring.

Significance of Formal Programming Experience for a Job in Data Science

Formal Programming experience is a critical part of a job or role in analytics and data science or technology; however, on-the-job learning is equally significant. 40% of the respondents feel that on the job learning balances Formal Programming Experience, and that both are Significant for a career in Analytics.

29% of the respondents feel that Formal Programming is very significant and on-the-job learning on its own is insufficient. 20% of the respondents believe that Formal Programming Experience is of Marginal significance and that on the job learning is sufficient. 11% of the respondents believe that Programming Skills are irrelevant for a data science job.

Significance of Prior Work Experience for a Career in Data Science

Prior work experience in a defined field or area lends significance to any future career or job prospect. For data science careers, 35% of the job seekers have experienced that prior experience of 5+ years is very significant for Analytics and Data Science hiring or jobs. 33% of the applicants feel that prior experience is significant but not crucial as similar experience in IT or Statistics is sufficient for a job or career in data science.

19% of the respondents feel that prior work experience is not required or necessary for a job in data science. 13% of the job seekers who responded to the survey feel that domain or industry is sufficient for a job in data science and that prior experience is of marginal significance.

Ease of Transition to Data Science and Analytics Roles from Non-Science Backgrounds

The ease of transition from one role to another role, especially across specialties or technical backgrounds can be difficult depending on the complexity of the domain or industry knowledge. For the analytics and data science domain, 48% of the job seekers feel that it is difficult to transition to Data Science from a Non-Science background, as skills and domain expertise specific to Data science roles require time and formal education or experience to master.

28% of the respondents believe that it is possible to transition as domain or industry expertise and some degree of technical know-how are sufficient for roles in Data Science. This is especially true for a role in BFSI or Pharma as domain experience and knowledge industry-specific processes and workflows are all important for an analytics career in these industries. While a technical education is important to have a career in Data Science or IT, it is possible to some extent in today’s environment to transition to a technology role through domain Expertise or with online learning and training.

13% of the respondents believe that the transition is easy with online training and free learning supporting the transition. However, 11% of the respondents feel that it is not possible for Non-science professionals to transition to a career in Data Science.

Best Approach to Get an Entry-level Job in Data Science

There are many approaches adopted by job seekers to enter a career or role in data science. The best approach identified by job seekers is Internship with Organizations, which comes immediately after completing a degree or program with an institute. 69% of the respondents believe that an internship is the best approach to get a foothold in a data science role in an organization, and this is significant as it lays emphasis on the networking at a very early stage to land an internship in an organization. Moreover, it places a great deal of weightage on industry-institute partnerships, which facilitate internships for graduating students.

43% of the respondents believe that the best approach is to Network and Collaborate across communities. Specific tech and data science communities, such as Github and StackOverflow are gaining popularity for showcasing skills and networking with professionals across companies for prospective projects (and jobs) in Data Science. The importance of Networking cannot be emphasized enough given the strength of this response.

40% of the participants believe that participation in Hackathons is the best approach to get an entry-level job. Many organizations now conduct recruitment focused hackathons to recruit and hire tech and data science talent. Moreover, Hackathons have emerged as a medium to showcase talent in the Data science domain, with many organizations sponsoring and monitoring hackathons to identify talent for specific roles. Hence, this approach is gaining popularity with both job seekers and firms alike.

Campus placements once the most preferred approach for a Technology job, is now the favourable approach for 29% of data science job seekers. While another popular approach in the past – Applying directly on Job portals and with Recruiters is now the approach for only 25% of the job applicants. Finally, approaching references across organizations and attending workshops are best approaches for 21% and 15% of the applicant audience, respectively.

Utilisation Of Massive Online Open Courses (MOOCs) For Re-Skilling After Hiring

Massive Online Open Courses or MOOCs are now extensively adopted by technology professionals to up-skill in a given domain or larger technology area. The adoption of MOOCs among the data science community is no different. 34% of the respondents mentioned that they Very Frequently Utilize MOOCs to Reskill and Upskill after Hiring. 30% of the respondents mentioned that they Frequently Utilize MOOCs to reskill and Upskill, while the same figure of 30% mentioned that they Occasionally Utilize MOOCs.

Resources or Tools Used to Up-skill or Prepare for Data Science Recruitment

Of all the resources and tools for up-skilling and preparing for recruitment, online self-paced learning has emerged as the most preferred method as 66% of the respondents have favoured this method for preparation and building capabilities. Online certifications are favoured by 27% of the respondents – this would fall in the category of online structured learning.

Online Assisted Learning, which is a blend of self-paced and structured learning, is favoured by 19% of the respondents. Forums for Networking and Engagement, such as Git Hub and Stack Overflow have emerged as preferred resources for preparation by 15% of the respondents. Workshops & Events, such as MLDS and Machine Con, are preferred by 15% of the respondents. Finally, other methods of upskilling are preferred by 8% of the respondents.

Industries and Sectors with the Most Opportunities in Data Science

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Of all the sectors covered, the broad IT sector has once again emerged as the sector that respondents feel provides the most opportunities for career in analytics and data science. Apart from the large range of opportunities that the IT sector provides, the significance of this in the current scenario is all the more compelling as the IT and ITES companies typically provide the maximum job security and stability in times of recessions and crisis. Hence, 41% of Data Science job seekers have identified this sector with the most opportunities.

In terms of opportunities, the IT sector is followed by the BFSI sector, which 32% of the job seekers have identified as the sector with the most opportunities. This is followed by the broad e-commerce and Digital Media sector. The growth of both these 2 industries over the last year signifies the opportunities available across analytics and data science in terms of customer segmentation and analytics – 22% of the respondents of the survey have identified these 2 sectors providing opportunities for data science job seekers.

From the job seekers’ perspective, Pharma & Healthcare has emerged as a sector that provides significant opportunities, with 11% of the respondents identifying this sector as the one with most opportunities. The remainder of the sectors Retail and Auto & Manufacturing have been affected by the recessionary trends and, according to applicants, offer 8% and 4% of opportunities respectively.

Sites or Resources Utilized to Find a Data Science Job

For specific sites or resources utilized to find a job in analytics or data science, LinkedIn has once again emerged at the top of the bracket across the Data Science job-seeking community.

This year, 82% of the respondents have mentioned that they utilize the professional networking site to find a job. This lends credence to a networking focused method of seeking jobs in not just the data science but also the broader technology sector. The leading job site is preferred by 21% of the job-seeking community.

Company Websites, where recruiters post their applications directly against opportunities or vacancies, has emerged as the preferred resource for 11% of the community. Connections and Networks is preferred by 7% of the community. Other sites, such as MonsterIndia,, TimesJobs, and are preferred by the rest of the community.

Areas of Greatest Interest for Job Seekers

Across all the industries and areas of greatest interest for job seekers, the broad Technology and IT domain is of greatest interest and preferred by about 56% of the job seekers in analytics and data science.

The BFSI sector emerges as the area of second preference with 41% of the respondents. Customer Analytics is preferred by 33% of the job seekers. This is followed by the Digital and Social Media analytics, which is preferred by 31% of the job seeker audience. Logistics and Supply-chain, the operations focused domain, is of interest for 29% of the job-seeking audience.

The upcoming sector around analytics in Smart Cities and Transport, which covers smart infrastructure, smart utilities, autonomous cars, connected cars, among others, is of interest to 21% of the audience. Sales and Marketing, which includes digital marketing, targeted audience segments, and sales forecasting is preferred by 20% of the audience.

Analytics in Government services, which would cover Agriculture and Social Initiatives, is emerging as a sector in which analytics professionals can make an impact and a difference, and hence has emerged as a preferred area of interest for 16% of the audience. The area of Customer Service, including customer support, service automation is the preferred area of interest for 12% of the audience.

Cities that Offer the Most Job & Recruitment Opportunities

Across all the cities that offer the most Data Science and Analytics opportunities, Bengaluru has once again emerged as the leading city among job seekers, with 87% of the job seeking audience voting Bengaluru as the destination for most opportunities.

Mumbai has emerged at the 2nd position with 4.5% of the audience identifying it as the destination for most job opportunities. This is followed by Delhi at 4% and Hyderabad at 2%.

The large gap between Bengaluru and the rest of the cities signifies the importance of India’s Silicon Valley in creating jobs and offering the maximum number of opportunities to the job seekers. By attracting technology companies, start-ups, and IT firms Bengaluru has emerged as the favoured destination for analytics opportunities.


As the overall Data Science and Analytics market evolves to adapt to the recession, it is important that both Analytics job seekers and the Data Science community understand the trends in hiring and get a pulse of the job market.

The job seeking community remains moderately optimistic and upbeat on the availability of jobs in the current environment and about a third of the community believes that jobs are available despite the recessionary environment.

The experience of the community during the job-hunting process reveals the following significant aspects of applying for data science jobs:

  • On-the-Job learning balances Formal Programming Experience, and both are significantly important for a career in Analytics
  • Prior experience of 5+ years is very significant for Analytics and Data Science hiring  
  • Almost half the job seekers feel that it is difficult to transition to Data Science from a Non-Science background
  • A large majority of the respondents believes that an internship is the best approach to get a foothold in a data science role in an organization – this emphasizes the importance of networking at a very early stage to land an internship in an organization.
  • About 2/3rd of the respondents have experienced that online self-paced learning has emerged as the most preferred method for preparation and building capabilities
  • A significant majority of the respondents utilize LinkedIn to find a job
  • IT and ITES companies have emerged as the industries with the most opportunities for job seekers
  • The job-seeking audience has overwhelming voted Bengaluru as the destination for most analytics and data science opportunities

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